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Lecture 1. 1
Financial Econometrics and Statistical
Arbitrage
Master of Science Program in Mathematical Finance
New York University
Administrative Details
Fall 2012
Farshid Magami Asl
G63.2707 - Financial Econometrics and

Volatility Forecasting II: Stochastic Volatility
Models, Miscellaneous Topics
Rob Reider
November 5, 2012
Rob Reider
Volatility Forecasting II: Stochastic Volatility Models, Miscellan
Comparison: GARCH Models and Stochastic Vol Models
As we discussed last

Volatility Forecasting I: GARCH Models
Rob Reider
October 22, 2012
Why Forecast Volatility
The three main purposes of forecasting volatility are for risk management, for asset allocation, and for taking bets on future volatility. A large part of risk mana

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Financial Econometrics and Statistical
Arbitrage
Master of Science Program in Mathematical Finance
New York University
Lecture 5
Fall 2012
Farshid Maghami Asl
G63.2707 - Financial Econometrics and Statistical Arbitrage
Co

Volatility Forecasting II: Stochastic Volatility Models
and Empirical Evidence
Rob Reider
November 5, 2012
Introduction to Stochastic Volatility Models
Assume that returns on an asset are given by rt = + t t as we did last week. In GARCHtype models, volat

Chapter 6
ARMA Models
6.1 ARMA Processes
In Section (4.6) we have introduced a special case (for p = 1 and q = 1) of a very
general class of stationary TS models called Autoregressive Moving Average
(ARMA) Models. In this section we will consider this cla

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Financial Econometrics and Statistical
Arbitrage
Master of Science Program in Mathematical Finance
New York University
Lecture 3
Fall 2012
Farshid Maghami Asl
G63.2707 - Financial Econometrics and Statistical Arbitrage
Co

Copyright Protected (Do Not Copy)
Financial Econometrics and Statistical
Arbitrage
Master of Science Program in Mathematical Finance
New York University
Lecture 4
Fall 2012
Farshid Maghami Asl
G63.2707 - Financial Econometrics and Statistical Arbitrage
Co

CHAPTER 4. STATIONARY TS MODELS
66
4.3 Moving Average Process MA(q)
Denition 4.5. cfw_Xt is a moving-average process of order q if
Xt = Zt + 1 Zt1 + . . . + q Ztq ,
(4.9)
where
Zt W N (0, 2 )
and 1 , . . . , q are constants.
Remark 4.6. Xt is a linear co

Copyright Protected (Do Not Copy)
Financial Econometrics and Statistical
Arbitrage
Master of Science Program in Mathematical Finance
New York University
Lecture 2
Fall 2012
Farshid Maghami Asl
G63.2707 - Financial Econometrics and Statistical Arbitrage
Co